A Blockchain-Based Incentive Mechanism for Sharing Cyber Threat Intelligence
ELECTRONICS(2023)
Abstract
With the development of the Internet, cyberattacks are becoming increasingly complex, sustained, and organized. Cyber threat intelligence sharing is one of the effective ways to alleviate the pressure on organizational or individual cyber security defense. However, the current cyber threat intelligence sharing lacks effective incentive mechanisms, resulting in mutual distrust and a lack of motivation to share among sharing members, making the security of sharing questionable. In this paper, we propose a blockchain-based cyber threat intelligence sharing mechanism (B-CTISM) to address the problems of free riding and lack of trust among sharing members faced in cyber threat intelligence sharing. We use evolutionary game theory to analyze the incentive strategy; the resulting evolutionarily stable strategy achieves the effect of promoting sharing and effectively curbing free-riding behavior. Then, the incentive strategy is deployed to smart contracts running in the trusted environment of blockchain, whose decentralization and tamper-evident properties can provide a trusted environment for participating members and establish trust without a third-party central institution to achieve secure and efficient cyber threat intelligence sharing. Finally, the effectiveness of the B-CTISM in facilitating and regulating threat intelligence sharing is verified through experimental simulation and comparative analysis.
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Key words
cyber threat intelligence,incentive mechanism,blockchain,evolutionary game theory,smart contracts
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